Zen now allows you to define `roles` for an external CLI and delegate work to another CLI via the new `clink` tool (short for `CLI + Link`). Gemini, for instance, offers 1000 free requests a day - this means you can save on tokens and your weekly limits within Claude Code by delegating work to another entirely capable CLI agent!
Define your own system prompts as `roles` and make another CLI do anything you'd like. Like the current tool you're connected to, the other CLI has complete access to your files and the current context. This also works incredibly well with Zen's `conversation continuity`.
feat: Azure OpenAI / Azure AI Foundry support. Models should be defined in conf/azure_models.json (or a custom path). See .env.example for environment variables or see readme. https://github.com/BeehiveInnovations/zen-mcp-server/issues/265
feat: OpenRouter / Custom Models / Azure can separately also use custom config paths now (see .env.example )
refactor: Model registry class made abstract, OpenRouter / Custom Provider / Azure OpenAI now subclass these
refactor: breaking change: `is_custom` property has been removed from model_capabilities.py (and thus custom_models.json) given each models are now read from separate configuration files
fix: restrictions should resolve canonical names for openrouter
fix: tools now correctly return restricted list by presenting model names in schema
fix: tests updated to ensure these manage their expected env vars properly
perf: cache model alias resolution to avoid repeated checks
fix: model definition re-introduced into the schema but intelligently and only a summary is generated per tool. Required to ensure CLI calls and uses the correct model
fix: removed `model` param from some tools where this wasn't needed
fix: fixed adherence to `*_ALLOWED_MODELS` by advertising only the allowed models to the CLI
fix: removed duplicates across providers when passing canonical names back to the CLI; the first enabled provider wins
docs: document provider base class
refactor: cleanup custom provider, it should only deal with `is_custom` model configurations
fix: make sure openrouter provider does not load `is_custom` models
fix: listmodels tool cleanup
Fixed issue where OpenAI models appeared twice in listmodels output by:
- Removing self-referencing aliases from OpenAI model definitions (e.g., "gpt-5" no longer includes "gpt-5" in its aliases)
- Adding filter in listmodels.py to skip aliases that match the model name
- Cleaned up inconsistent alias naming (o3-pro -> o3pro)
This ensures each model appears only once in the listing while preserving all useful aliases.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Address code review feedback by creating ModelContext instance once
at the beginning of _consult_model method instead of creating it twice.
- Move ModelContext import to method beginning for better practice
- Create single ModelContext instance and reuse for both file processing
and temperature validation
- Remove redundant ModelContext creation on line 558
- Improve code clarity and efficiency as suggested by code review
Fixed runtime bug where _prepare_file_content_for_prompt was called
without required model_context parameter, causing RuntimeError when
processing requests with relevant_files.
- Create ModelContext instance with model_name in _consult_model method
- Pass model_context parameter to _prepare_file_content_for_prompt call
- Add comprehensive regression test to prevent future occurrences
- Maintain consensus tool's blinded design with independent model contexts
- Fix ModelContext constructor call in consensus tool (remove invalid parameters)
- Refactor temperature pattern matching for better readability per code review
- All tests now passing (799/799 passed)
- Fix consensus tool hardcoded temperature=0.2 bypassing model capabilities
- Add intelligent temperature inference for unknown custom models
- Support multi-model collaboration (O3, Gemini, Claude, Mistral, DeepSeek)
- Only OpenAI O-series and DeepSeek reasoner models reject temperature
- Most reasoning models (Gemini Pro, Claude, Mistral) DO support temperature
- Comprehensive logging for temperature decisions and user guidance
Resolves: https://github.com/BeehiveInnovations/zen-mcp-server/issues/245
Disabled secondary tools by default (for new installations), updated README.md with instructions on how to enable these in .env
run-server.sh now displays disabled / enabled tools (when DISABLED_TOOLS is set)
fix: Minor tweaks to prompts
fix: Improved support for smaller models that struggle with strict structured JSON output
Rearranged reasons to use the MCP above quick start (collapsed)
This commit updates all references to Claude Opus 4 and Sonnet 4 to their newer 4.1 versions throughout the codebase.
The changes include:
- Updating model names in `conf/custom_models.json` and `providers/dial.py`.
- Updating aliases and descriptions to match the new model versions.
- Updating `.env.example` to reflect the new model names.
- Updating all relevant test suites to use the new model names and ensure all tests pass.
